Amazon Aurora: Best Practices

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Kim Schmidt

3:59:33

32 View

0. Course Overview

0. Course Overview.mp4

02:05

1. Understanding Amazon Auroras Amazing Architecture

0. Amazon Aurora A Relational Database Built for the Cloud.mp4

04:20

1. Amazon Auroras Managed Service and Aurora Serverless Features.mp4

03:46

2. Amazon Auroras Architectural Improvements.mp4

03:22

3. An Awesome Look at Amazon Auroras Database and Storage Node IO.mp4

06:55

4. Amazon Auroras Connection Capabilities and Fast COMMITs.mp4

03:05

5. Amazon Auroras Log-structured Storage and Indexing.mp4

03:29

6. Amazon Auroras Survivable Cache and Instant Crash Recovery.mp4

01:53

7. Your Job as a Database Solutions Architect.mp4

02:06

8. Amazon Aurora Key Architectural Takeaways.mp4

01:27

2. Introducing Amazon Auroras Resulting Feature Improvements

0. Recap of Amazon Auroras Architectural Improvements.mp4

01:58

1. Amazon Auroras Performance Improvements.mp4

05:52

2. Amazon Auroras Scalability Improvements.mp4

05:10

3. Amazon Auroras High Performance and Durability Improvements.mp4

06:02

4. Amazon Auroras Security Improvements.mp4

08:01

5. Amazon Aurora Key Feature Improvement Takeaways.mp4

01:22

3. Building and Launching Amazon Aurora Clusters

0. Amazon Aurora Endpoints.mp4

04:04

1. Amazon Aurora Instance Class Types.mp4

02:44

2. Comparing Amazon Aurora MySQL, PostgreSQL, and Serverless.mp4

04:23

3. Demo Creating, Configuring, Launching, and Connecting to Amazon Aurora Clusters.mp4

04:55

4. Demo Working with Amazon Aurora Clusters Remotely.mp4

04:00

5. Creating, Configuring, and Working with Amazon Aurora Clusters Key Takeaways.mp4

01:06

4. Managing and Maintaining Amazon Aurora Clusters

0. Starting and Stopping Aurora Clusters.mp4

02:55

1. Demo Modifying Amazon Aurora Clusters and Instances.mp4

03:35

2. Demo Adding an Amazon Aurora Read Replica and Adding an AutoScaling Policy.mp4

06:53

3. Amazon Aurora Instance Actions.mp4

00:52

4. Amazon Aurora Database Parameter Groups.mp4

04:31

5. Managing Amazon Aurora Performance and Scaling.mp4

02:26

6. Displaying Amazon Aurora Cluster Volume Status.mp4

01:07

7. Amazon Auroras Integration with Other AWS Services.mp4

01:25

8. Maintaining an Amazon Aurora Database Cluster.mp4

03:43

9. Amazon Aurora Key Management and Maintenance Takeaways.mp4

01:01

5. Securing Amazon Aurora

0. Primary Database Security Vulnerabilities and AWS Solutions.mp4

05:17

1. AWS Shared Responsibility Model and AWS Well Architected Frameworks Security Pillar.mp4

02:24

2. Managing Access to Amazon Aurora Resources.mp4

01:46

3. Amazon Aurora Data Protection.mp4

03:34

4. Amazon Aurora Encryption.mp4

02:00

5. How Amazon Aurora Works with IAM.mp4

02:47

6. Rotating Amazon Aurora Credentials Using AWS Secrets Manager.mp4

02:55

7. Amazon Aurora Key Security Takeaways.mp4

01:42

6. Logging, Monitoring, and Auditing Amazon Aurora Clusters

0. Amazon Aurora Metrics to Watch.mp4

03:54

1. Monitoring Tools for Amazon Aurora.mp4

03:01

2. Demo Monitoring Amazon Aurora with Amazon CloudWatch.mp4

03:54

3. Monitoring Amazon Aurora Database Logs with Amazon CloudWatch.mp4

01:04

4. Amazon Aurora Metrics in the RDS Console.mp4

03:01

5. Monitoring Amazon Aurora with Performance Insights.mp4

03:51

6. Amazon Aurora Recommendations, Database Activity Monitoring, and Events.mp4

02:51

7. Auditing Amazon Aurora.mp4

02:58

8. Amazon Aurora Key Logging, Monitoring, and Auditing Takeaways.mp4

01:04

7. Exploring Amazon Auroras Unique Backup and Restore Strategies

0. Backing up and Restoring an Amazon Aurora Cluster.mp4

02:27

1. Amazon Aurora Backups, Snapshots, and PITR.mp4

03:02

2. Demo Working with Amazon Aurora Snapshots.mp4

05:13

3. Using Amazon Aurora Database Cloning vs. PITR.mp4

03:41

4. Using Amazon Aurora Backtrack vs. PITR.mp4

03:01

5. Using Amazon Aurora Cross-region Read Replicas and Global Database for Restoration.mp4

01:54

6. Amazon Aurora Key Backup and Restore Takeaways.mp4

01:15

8. Examining Amazon Aurora Data Migration Strategies

0. Data Migration to an Amazon Aurora Cluster.mp4

01:35

1. Migrating to Amazon Aurora MySQL.mp4

03:41

2. Migrating to Amazon Aurora PostgreSQL.mp4

03:49

3. Migrating to Amazon Aurora Using AWS Database Migration Service.mp4

04:12

4. Large-scale Migrations to Amazon Aurora Using AWS Snowball.mp4

02:09

5. Heterogeneous Migrations Using AWS Schema Conversion Tool.mp4

01:12

6. Amazon Aurora Key Data Migration Takeaways.mp4

01:17

9. Designing Amazon Aurora Test Environments

0. Amazon Aurora Database Cloning for Test Environments.mp4

02:53

1. Amazon Aurora Serverless and AWS DMS Test Environments.mp4

02:36

2. Restoring Data in Test Environments.mp4

01:41

3. Using T3 Instances in Test Environments.mp4

01:24

4. Amazon Aurora Key Test Environment Takeaways.mp4

01:13

10. Troubleshooting Amazon Aurora

0. Troubleshooting Amazon Aurora.mp4

01:04

1. Troubleshooting Amazon Aurora Connection Issues.mp4

02:46

2. Troubleshooting Amazon Aurora Security Issues.mp4

01:07

3. Troubleshooting Amazon Aurora Outages, Reboots, and Parameter Changes.mp4

02:04

4. Troubleshooting Amazon Aurora Out-of-Memory Issues.mp4

02:21

5. Troubleshooting Amazon Aurora Replica Lag.mp4

02:15

6. Troubleshooting Amazon Aurora Replica Failures.mp4

02:02

7. Troubleshooting Amazon Aurora Disk Space Errors.mp4

01:15

8. Troubleshooting Applications Using Amazon Aurora.mp4

01:50

9. Amazon Aurora Key Troubleshooting Takeaways.mp4

01:59

11. Recognizing Amazon Auroras Extended Capabilities

0. Amazon Auroras Unique Capabilities.mp4

02:55

1. Amazon Aurora Parallel Query OLTP and OLAP.mp4

04:30

2. Amazon Aurora Machine Learning.mp4

02:53

3. Amazon Aurora Integration with Other AWS State-of-the-art Services.mp4

02:20

4. Amazon Aurora Key Extended Capabilities Takeaways.mp4

01:21

Description

Amazon Aurora has revolutionized relational databases. This course will teach you everything you need to know about Amazon Aurora’s amazing superiority over other RDBMS and how to work with it using best practices.

What You'll Learn?

Amazon Aurora is a relational database built for the cloud. In this course, Amazon Aurora: Best Practices, you’ll learn to leverage Aurora’s scalability, high performance, high availability, durability, and security while taking advantage of the management tasks that are managed for you. First, you’ll explore the architectural improvements that make Aurora a cut above the competition. Next, you’ll discover the feature improvements that this architecture enables, as well as how to efficiently and effectively design, deploy, access, monitor, use, and maintain Amazon Aurora clusters to improve performance, reduce costs, and jumpstart data transformation and innovation. Finally, you’ll learn how to utilize advanced functionalities like data migration, schema conversion, and troubleshooting techniques. When you’re finished with this course, you’ll have the skills and knowledge of Amazon Aurora needed to utilize AWS’s relational database for traditional relational database functionalities, and also know what it can for machine learning and artificial intelligence.

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Database Programming

Amazon AWS

Kim Schmidt

Instructor's Courses

Kim Schmidt has been working in the technology industry for more than 12 years with an extremely broad array of titles and using very diverse technologies. She holds many industry certifications and awards. Companies Kim has worked for or with include Microsoft, Dun & Bradstreet, Google, Amazon Web Services, and a couple of Augmented Reality companies. Kim is the Founder and CEO of DataLeader, an AWS Partner and Vendor company. DataLeader focuses on AWS Big Data Architecture, Data Solutions, Advanced Analytics, AI and ML. Kim has written white papers and has done many other projects for AWS, including speaking engagements throughout the year, and has contracted for many of the leading data and analytics independent software vendors in AWS Marketplace. Kim’s first participation at AWS’ annual conference, re:Invent, was in 2015 on big data architecture. At AWS re:Invent 2017, Kim presented 2, 2.5-hour Workshops on “Comprehensive Big Data Architecture Made Easy”. The demos and hands-on exercises can be found in video format at http://aws-kimschmidt.com/ . Kim recently was on an Expert Panel at Interop ITX https://www.interop.com/ on “The Future of Data Jobs: Innovation, Security, Automation and the Cloud” as well as present a session entitled “AI/ML Your Apps & Business Processes”. Kim has been working on a book entitled, “Artificial Intelligence & Analytics on AWS.” On her book’s website, https://ai-advanced-insights-aws.co/ you can download a sample 100+ page chapter on “Serverless Predictive Analytics” using Amazon SageMaker, Amazon DynamoDB, AWS Lambda, and Machine Learning models. She blogs at https://awskimschmidt.com/ and https://kimschmidtsbrain.com/ and she has many AWS videos on her YouTube channel, https://www.youtube.com/c/DataLeader .

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Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.